Finding Many Sparse Cuts Using Entropy Maximization
Probability
2022-03-16 v1 Computational Engineering, Finance, and Science
Discrete Mathematics
Abstract
A randomized algorithm for finding sparse cuts is given which is based on constructing a dual markov chain called multiscale rings process(MRP) and a new concept of entropy. It is shown how the time to absorption of the dual process measures the connectedness of the graph and mixing of the corresponding markov process which is then utilized to do clustering. The second algorithm uses the entropy which provides a new methodology and a set of tools to think about sparse cuts as well as sparsification of a graph.
Cite
@article{arxiv.2203.07869,
title = {Finding Many Sparse Cuts Using Entropy Maximization},
author = {Farshad Noravesh},
journal= {arXiv preprint arXiv:2203.07869},
year = {2022}
}
Comments
2 figures